__add__ fails for empty array inputs

[mitkotak]

Here's the MWE

>>> import pycuda.autoinit
>>> import pycuda.gpuarray as gpuarray
>>> import numpy as np
>>> empty_array = np.array([])
>>> empty_array_gpu = gpuarray.to_gpu(empty_array)
>>> result_array = empty_array + 0 # array([], dtype=float64)
>>> result_array_gpu = -empty_array_gpu + 0 # Fails

Here's the error trace

---------------------------------------------------------------------------
ArgumentError                             Traceback (most recent call last)
Input In [29], in <cell line: 1>()
----> 1 empty_array_gpu + 0

File ~/pycuda/pycuda/gpuarray.py:593, in GPUArray.__add__(self, other)
    590 elif np.isscalar(other):
    591     # add a scalar
    592     if other == 0:
--> 593         return self.copy()
    594     else:
    595         result = self._new_like_me(_get_common_dtype(self, other))

File ~/pycuda/pycuda/gpuarray.py:393, in GPUArray.copy(self)
    391 def copy(self):
    392     new = GPUArray(self.shape, self.dtype, self.allocator)
--> 393     _memcpy_discontig(new, self)
    394     return new

File ~/pycuda/pycuda/gpuarray.py:1570, in _memcpy_discontig(dst, src, async_, stream)
   1566         drv.memcpy_dtod_async(
   1567             dst.gpudata, src.gpudata, src.nbytes, stream=stream
   1568         )
   1569     else:
-> 1570         drv.memcpy_dtod(dst.gpudata, src.gpudata, src.nbytes)
   1571 else:
   1572     # The arrays might be contiguous in the sense of
   1573     # having no gaps, but the axes could be transposed
   1574     # so that the order is neither Fortran or C.
   1575     # So, we attempt to get a contiguous view of dst.
   1576     dst = _as_strided(dst, shape=(dst.size,), strides=(dst.dtype.itemsize,))

ArgumentError: Python argument types in
    pycuda._driver.memcpy_dtod(NoneType, NoneType, int)
did not match C++ signature:
    memcpy_dtod(unsigned long long dest, unsigned long long src, unsigned long size)